Generative AI (genAI) tools (e.g., ChatGPT, Copilot) have become ubiquitous in software engineering (SE). As SE educators, it behooves us to understand the consequences of genAI usage among SE students and to create a holistic view of where these tools can be successfully used. Through 16 reflective interviews with SE students, we explored their academic experiences of using genAI tools to complement SE learning and implementations. We uncover the contexts where these tools are helpful and where they pose challenges, along with examining why these challenges arise and how they impact students. We validated our findings through member checking and triangulation with instructors. Our findings provide practical considerations of where and why genAI should (not) be used in the context of supporting SE students.

Background: The sustainability of Open Source Software (OSS) projects relies on attracting and retaining contributors. Interpersonal challenges, whether experienced or witnessed, can discourage participation, alter behavior, or drive contributors away. Aims: This study examines how interpersonal challenges in OSS communities persist over time and explores their behavioral consequences on contributors' decisions and actions. Method: We analyze data from two large GitHub Open Source surveys conducted in$2017(\mathrm{n}=5,495)$and$2024(\mathrm{n}=8,452)$, evaluating changes in reported interpersonal challenges (RQ1) and differential consequences of exposure between 2017 and 2024 (RQ2). Results: Our findings reveal a significant increase in reported interpersonal challenges in 2024 compared to 2017. Contributors more frequently reported severe challenges such as threats of violence, impersonation, sustained harassment, stalking, and doxxing. The behavioral impact has shifted: experiencing rudeness, stalking, and name-calling became strongly linked to stopping contributions, adopting pseudonyms, working privately, and avoiding offline events. Witnessing harmful behaviors like name-calling and impersonation also became stronger predictors of working privately or advocating for Codes of Conduct. These trends show toxicity is not only more pervasive but increasingly damaging to OSS participation and community health. Conclusions: Results highlight a concerning rise in interpersonal challenges within OSS communities, with rudeness emerging as the most impactful. The growing influence of toxic behaviors on contributors' decisions to withdraw, conceal identities, isolate collaboration, and avoid offline engagement underscores the urgent need for stronger, proactive community support. Sustaining healthy OSS projects requires both technical excellence and deliberate investment in social infrastructure to foster respectful collaboration spaces.

Background: With limited job openings and growing selectivity in tech, understanding the skills hiring managers expect from entry-level Software Engineering candidates is essential. While job postings emphasize technical abilities, success often hinges on non-technical skills, as interpersonal and adaptive abilities. Yet, mismatches between candidate profiles and employer expectations lead to inefficient hiring and missed opportunities. Aims: We investigated which skills hiring managers expect from early-career Software Engineering (SE) candidates and how those skills are described in job postings. Method: To achieve this goal, we conducted an exploratory case study in Hewlett Packard Enterprise (HPE), a global technology company. We interviewed 12 managers, collected seven HPE job postings related to entry-level positions in Software Engineering-related roles, and employed mixed methods to analyze the data. Results: Our findings show that hiring managers place strong emphasis on non-technical expectations when evaluating entry-level candidates. They commonly believe that technical competencies can be taught on the job, provided the candidate demonstrates the right nontechnical attributes. The non-technical expectations included adaptability, proactivity, dependability, self-direction, passion, collaboration, communication, problem solving, courage, selfawareness, self-confidence, willingness to learn, and having a process-oriented mindset. Conclusions: To secure their first job, Software Engineering students should invest not only in technical competencies but also in developing non-technical skills. Our findings show that hiring managers prioritize these skills, even though they are often underrepresented in job postings. Making such expectations more visible could help bridge the gap between candidates and employers, leading to more efficient and effective hiring.

Generative AI (genAI) tools, such as ChatGPT or Copilot, are advertised to improve developer productivity and are being integrated into software development. However, misaligned trust, skepticism, and usability concerns can impede the adoption of such tools. Research also indicates that AI can be exclusionary, failing to support diverse users adequately. One such aspect of diversity is cognitive diversity-variations in users' cognitive styles-that leads to divergence in perspectives and interaction styles. When an individual's cognitive style is unsupported, it creates barriers to technology adoption. Therefore, to understand how to effectively integrate genAI tools into software development, it is first important to model what factors affect developers' trust and intentions to adopt genAI tools in practice? We developed a theoretically grounded statistical model to (1) identify factors that influence developers' trust in genAI tools and (2) examine the relationship between developers' trust, cognitive styles, and their intentions to use these tools in their work. We surveyed software developers ($\mathrm{N}=238$) at two major global tech organizations: GitHub Inc. and Microsoft; and employed Partial Least Squares-Structural Equation Modeling (PLS-SEM) to evaluate our model. Our findings reveal that genAI's system/output quality, functional value, and goal maintenance significantly influence developers' trust in these tools. Furthermore, developers' trust and cognitive styles influence their intentions to use these tools in their work. We offer practical suggestions for designing genAI tools for effective use and inclusive user experience.

The sustainability of open source software (OSS) projects hinges on contributor retention. Interpersonal challenges can inhibit a feeling of welcomeness among contributors, particularly from underrepresented groups, which impacts their decision to continue with the project. How much this impact is, varies among individuals, underlining the importance of a thorough understanding of their effects. Here, we investigate the effects of interpersonal challenges on the sense of welcomeness among diverse populations within OSS, through the diversity lenses of gender, race, and (dis)ability. We analyzed the large-scale Linux Foundation Diversity and Inclusion survey (n = 706) to model a theoretical framework linking interpersonal challenges with the sense of welcomeness through Structural Equation Models Partial Least Squares (PLS-SEM). We then examine the model to identify the impact of these challenges on different demographics through Multi-Group Analysis (MGA). Finally, we conducted a regression analysis to investigate how differently people from different demographics experience different types of interpersonal challenges. Our findings confirm the negative association between interpersonal challenges and the feeling of welcomeness in OSS, with this relationship being more pronounced among gender minorities and people with disabilities. We found that different challenges have unique impacts on how people feel welcomed, with variations across gender, race, and disability groups. We also provide evidence that people from gender minorities and with disabilities are more likely to experience interpersonal challenges than their counterparts, especially when we analyze stalking, sexual harassment, and doxxing. Our insights benefit OSS communities, informing potential strategies to improve the landscape of interpersonal relationships, ultimately fostering more inclusive and welcoming communities.

Introduction : Digital products increasingly reshape industries, influencing human behavior and decision-making. However, the software development teams developing these systems often lack diversity, which may lead to designs that overlook the needs, equal treatment or safety of diverse user groups. These risks highlight the need for fostering diversity and inclusion in software development to create safer, more equitable technology. Method : This research is based on insights from an academic meeting in June 2023 involving 23 software engineering researchers and practitioners. We used the collaborative discussion method 1-2-4-ALL as a systematic research approach and identified six themes around the theme “challenges and opportunities to improve Software Developer Diversity and Inclusion (SDDI).” We identified benefits, harms, and future research directions for the four main themes. Then, we discuss the remaining two themes, AI & SDDI and AI & Computer Science education, which have a cross-cutting effect on the other themes. Results : This research explores the key challenges and research opportunities for promoting SDDI, providing a roadmap to guide both researchers and practitioners. We underline that research around SDDI requires a constant focus on maximizing benefits while minimizing harms, especially to vulnerable groups. As a research community, we must strike this balance in a responsible way.

Feeling part of a group is a basic human need that significantly influences an individual's behavior, long-term engagement, and job satisfaction. A strong sense of belonging holds particular importance within software delivery teams, which grapple with challenges related to well-being and employee retention. However, the specific factors closely associated with the sense of belonging in the context of software delivery teams remain largely unknown. Without a clear understanding of these factors, organizations' efforts to promote a sense of belonging and diversity and inclusion more broadly may prove ineffective. Based on existing literature, we identified key factors potentially relevant to the sense of belonging in software delivery teams, such as work appreciation and psychological safety, and investigated the interrelation among these factors. We surveyed members of software delivery teams (n=10,781) of a major software delivery organization and used Partial Least Squares-Structural Equation Modeling (PLS-SEM) to evaluate a theoretical model to understand the factors that might contribute to a sense of belonging to the team. We also conducted a multi-group analysis to evaluate how the associations change based on individuals' leadership involvement and an importance-performance map analysis to find the most critical indicators of belongingness. Our findings indicate a positive association between psychological safety and work appreciation and belonging to the team. Women feel less belonging than men, especially those not in leadership positions. Authoritativeness is negatively associated with belonging, and tenure is positively associated with belonging regardless of the role. Through this research, we seek to provide insights into the sense of belonging to the team and foster a more inclusive and cohesive work environment.

In this study of burnout and engagement, we address three major themes. First, we offer a review of prior studies of burnout among IT professionals and link these studies to the Job Demands-Resources (JD-R) model. Informed by the JD-R model, we identify three factors that are organizational job resources and posit that these (a) increase engagement and (b) decrease burnout. Second, we extend the JD-R by considering software professionals’ intention to stay as a consequence of these two affective states, burnout and engagement. Third, we focus on the importance of factors for intention to stay, and actual retention behavior. We use a unique dataset of over 13,000 respondents at one global IT organization, enriched with employment status 90 days after the initial survey. Leveraging partial-least squares structural quation modeling and machine learning, we find that the data mostly support our theoretical model, with some variation across different subgroups of respondents. An importance-performance map analysis suggests that managers may wish to focus on interventions regarding burnout as a predictor of intention to leave. The Machine Learning model suggests that engagement and opportunities to learn are the top two most important factors that explain whether software professionals leave an organization.

The sense of belonging to a community is a basic human need that impacts an individual's behavior, long-term engagement, and job satisfaction, as revealed by research in disciplines such as psychology, healthcare, and education. Despite much research on how to retain developers in Open Source Software (OSS) projects and other virtual, peer-production communities, there is a paucity of research investigating what might contribute to a sense of belonging in these communities. To that end, we develop a theoretical model that seeks to understand the link between OSS developer motives and a Sense of Virtual Community (SVC). We test the model with a dataset collected in the Linux Kernel developer community (N=225), using structural equation modeling techniques. Our results for this case study show that intrinsic motivations (social or hedonic motives) are positively associated with a sense of virtual community, but living in an authoritative country and being paid to contribute can reduce the sense of virtual community. Based on these results, we offer suggestions for open source projects to foster a sense of virtual community, with a view to retaining contributors and Improving projects' sustainability.

[Background] Selecting an appropriate task is challenging for Open Source Software (OSS) project newcomers and a variety of strategies can help them in this process. [Aims] In this research, we compare the perspective of maintainers, newcomers, and existing contributors about the importance of strategies to support this process. Our goal is to identify possible gulfs of expectations between newcomers who are meant to be helped and contributors who have to put effort into these strategies, which can create friction and impede the usefulness of the strategies. [Method] We interviewed maintainers (n=17) and applied inductive qualitative analysis to derive a model of strategies meant to be adopted by newcomers and communities. Next, we sent a questionnaire (n=64) to maintainers, frequent contributors, and newcomers, asking them to rank these strategies based on their importance. We used the Schulze method to compare the different rankings from the different types of contributors. [Results] Maintainers and contributors diverged in their opinions about the relative importance of various strategies. The results suggest that newcomers want a better contribution process and more support to onboard, while maintainers expect to solve questions using the available communication channels. [Conclusions] The gaps in perspectives between newcomers and existing contributors create a gulf of expectation. OSS communities can leverage our results to prioritize the strategies considered the most important by newcomers.

Women are underrepresented in Open Source Software (OSS) projects, as a result of which, not only do women lose career and skill development opportunities, but the projects themselves suffer from a lack of diversity of perspectives. Practitioners and researchers need to understand more about the phenomenon; however, studies about women in open source are spread across multiple fields, including information systems, software engineering, and social science. This article systematically maps, aggregates, and synthesizes the state-of-the-art on women’s participation in OSS. It focuses on women contributors’ representation and demographics, how they contribute, their motivations and challenges, and strategies employed by communities to attract and retain women. We identified 51 articles (published between 2000 and 2021) that investigated women’s participation in OSS. We found evidence in these papers about who are the women who contribute, what motivates them to contribute, what types of contributions they make, challenges they face, and strategies proposed to support their participation. According to these studies, only about 5% of projects were reported to have women as core developers, and women authored less than 5% of pull-requests, but had similar or even higher rates of pull-request acceptances than men. Women make both code and non-code contributions, and their motivations to contribute include learning new skills, altruism, reciprocity, and kinship. Challenges that women face in OSS are mainly social, including lack of peer parity and non-inclusive communication from a toxic culture. We found 10 strategies reported in the literature, which we mapped to the reported challenges. Based on these results, we provide guidelines for future research and practice.

Success in Open Source Software (OSS) is often perceived as an exclusively code-centric endeavor. This perception can exclude a variety of individuals with a diverse set of skills and backgrounds, in turn helping exacerbate the current diversity & inclusion imbalance in OSS. Because one's perspective of success can affect one's personal, professional, and life choices, to support a diverse class of individuals we must first understand how OSS contributors understand success. Thus far, research has used a uni-dimensional, code-centric lens to define success. In this paper, we challenge this status quo to reveal OSS contributors’ multifaceted definitions of success. We do so through interviews with 27 OSS contributors whose communities recognize them as successful, and a follow-up open survey with 193 OSS contributors. Our study provides nuanced definitions of success perceptions in OSS, which might help devise strategies to attract and retain a diverse set of contributors, helping them attain their unique “pot of gold at the end of the rainbow”.

Open Source Software (OSS) has changed drastically over the last decade, with OSS projects now producing a large ecosystem of popular products, involving industry participation, and providing professional career opportunities. But our field's understanding of what motivates people to contribute to OSS is still fundamentally grounded in studies from the early 2000s. With the changed landscape of OSS, it is very likely that motivations to join OSS have also evolved. Through a survey of 242 OSS contributors, we investigate shifts in motivation from three perspectives: (1) the impact of the new OSS landscape, (2) the impact of individuals' personal growth as they become part of OSS communities, and (3) the impact of differences in individuals' demographics. Our results show that some motivations related to social aspects and reputation increased in frequency and that some intrinsic and internalized motivations, such as learning and intellectual stimulation, are still highly relevant. We also found that contributing to OSS often transforms extrinsic motivations to intrinsic, and that while experienced contributors often shift toward altruism, novices often shift toward career, fun, kinship, and learning. OSS projects can leverage our results to revisit current strategies to attract and retain contributors, and researchers and tool builders can better support the design of new studies and tools to engage and support OSS development.

Open Source Software projects add labels to open issues to help contributors choose tasks. However, manually labeling issues is time-consuming and error-prone. Current automatic approaches for creating labels are mostly limited to classifying issues as a bug/non-bug. In this paper, we investigate the feasibility and relevance of labeling issues with the domain of the APIs required to complete the tasks. We leverage the issues' description and the project history to build prediction models, which resulted in precision up to 82% and recall up to 97.8%. We also ran a user study (n=74) to assess these labels' relevancy to potential contributors. The results show that the labels were useful to participants in choosing tasks, and the API-domain labels were selected more often than the existing architecture-based labels. Our results can inspire the creation of tools to automatically label issues, helping developers to find tasks that better match their skills.

Open source communities hosted in large foundations operate in a complex socio-technical ecosystem, which includes a heterogeneous mix of projects and stakeholders. Previous work has thus far investigated the challenges faced in OSS communities from the point of view of specific stakeholders, primarily at the level of individual projects. None have yet studied the challenges faced within a large, federated open source organization. In this paper, we aim to bridge this gap to identify ongoing challenges contributors face in a mature OSS organization. To do so, we surveyed 624 contributors at the Apache Software Foundation (ASF) and ran 11 semi-structured follow up interviews. We validated our findings through member checking with the interviewees as well as the ASF Diversity and Inclusion (D&I) committee. The contributions of this paper include: (1) an empirically-evidenced conceptual model of the 88 challenges that contributors face in a mature OSS foundation and (2) a set of 48 community-recommended strategies for alleviating these challenges. Our results show that even well-established and mature organizations still face a variety of individual and project-specific challenges and that it is difficult to design a comprehensive set of processes and guidelines to match the needs and expectations of a diverse and large federated community. Our conceptual challenges model and associated strategies to mitigate them can provide guidance to other OSS foundations and projects helping them in building better support processes and tools to create a successful, thriving community of contributors.

Software developers who want to start contributing to an Open Source Software (OSS) project often struggle to find appropriate first tasks. The voluntary, self-organizing distribution of decentralized labor and the distinct nature of some OSS projects intensifies this challenge. Mentors, who work closely with newcomers, develop strategies to recommend tasks. However, to date neither the challenges mentors face in recommending tasks nor their strategies have been formally documented or studied. In this paper, we interviewed mentors of well-established OSS projects (n=10) and qualitatively analyzed their answers to identify both challenges and strategies related to recommending tasks for newcomers. Then, we employed a survey (n=30) to map the strategies to challenges and collect additional strategies. Our study identified 7 challenges and 13 strategies related to task recommendation. Strategies such as "tagging the issues based on difficulty," "adding documentation," "assigning a small task first and then challenge the newcomers with bigger tasks," and "dividing tasks into smaller pieces" were frequently mentioned as ways to overcome multiple challenges. Our results provide insights for mentors about the strategies OSS communities can use to guide their mentors and for tool builders who design automated support for task assignment.

Open Source Software (OSS) development is a collaborative endeavor where expert developers, distributed around the globe create software solutions. Given this characteristic, OSS communities have been studied as technical communities, where stakeholders join and evolve in their careers based on their (often voluntary) code contributions to the project. However, the OSS landscape is slowly changing with more people and companies getting involved in OSS. This means that projects now need people in non-technical roles and activities to keep the project sustainable and evolving. In this paper, we focus on understanding the roles and activities that are part of the current OSS landscape and the different career pathways in OSS. By conducting and analyzing 17 interviews with OSS contributors who are well known in the community, we provide empirical evidence of the existence and importance of community-centric roles (e.g advocate, license manager, community founder) in addition to the well-known project-centric ones (e.g maintainer, core member). However, the community-centric roles typically remain hidden, since these roles may not leave traces in software repositories typically analyzed by researchers. We found that people can build a career in OSS through different roles and activities, with different backgrounds, including those not related to writing software. Furthermore, people's career pathways are fluid, moving between project and community-centric roles. Our work highlights that communities and researchers need to take action to acknowledge the importance of these varied roles, making these roles visible and well-recognized, which can ultimately help attract and retain more people in the OSS projects.

Background: Aligning IT to business goals is a top priority for CIOs. However, managers in the IT Service Industry face difficulties to define and monitor IT service goals and strategies aligned to business goals. Goal: We carried out a study to investigate how IT service managers define, measure and monitor IT service goals and strategies, and the difficulties they have faced in this context. Method: We interviewed five IT service managers from four service provider organizations and used coding procedures to analyze the collected data. Results: We obtained information about how organizations define, measure and evaluate IT service goals and strategies and, from the difficulties reported by the managers, we identified 19 pitfalls. Conclusions: By analyzing the relations among the pitfalls, we defined five hypotheses: (i) lack of awareness and transparency on the relationship between strategies and goals may harm the achievement of IT service goals and strategies, (ii) lack of proper support to execute measurement inhibits reevaluation and adjustment of strategies and indicators related to IT service goals, (iii) lack of motivation can jeopardize decision-making by IT service managers, (iv) conflicts between strategies may harm IT service goals achievement, and (v) lack of proper support to execute IT service management initiatives may harm IT service goals achievement.

GQM+Strategies is a goal-oriented measurement approach that supports organizations in identifying goals, strategies to achieve goals, and measures to monitor strategies and goals. However, identifying proper strategies is not an easy task. This paper presents two studies performed to investigate how strategies can be established to achieve IT service goals. First, we carried out a qualitative study involving three IT service-related departments of a large company to find out how they have been defining strategies and problems faced. We noted that strategies were defined by leaders, in a top-down approach, or by teams, in a bottom-up approach, and causal analysis techniques have been used to investigate aspects which can impact goals achievement. We also found the relation between the IT service strategies and goals was not clear for the teams. Considering these findings, we performed an empirical study in another IT-service related department applying an approach combining GQM+Strategies plus some instruments (checklists, templates and examples) and causal analysis to support IT strategies identification. As a result, we noticed that by using that approach the team was able to derive IT strategies based on goals, define measures to monitor goals and strategies, and better understand the alignment between the goals to be achieved and the strategies to be performed. Moreover, results showed that causal analysis is useful to define strategies and that supporting instruments facilitate using the approach and building GQM+Strategies grid.

Background: Businesses are increasingly dependent on IT services, and providers need to deliver fast, with high quality and low cost.An incident is an event that can lead to loss or disruption of services.Incident management reinstates normal service operation as quickly as possible and mitigates negative impact to business, ensuring agreed levels of service quality.So, reduce resolution time is usually the most important goal for incidents.Aims We aim to obtain knowledge about process and identify adequate metrics for Incident Management to help reduction of resolution time.Our research questions are: (i) Which Incident Management sub-process is causing more impact to resolution time?(ii) Which metrics can be used to measure this sub-process?(iii) What actions can be taken to improve Incident Management process in order to reduce impact of this subprocess in resolution time?Method: We present a case study in a global large company that considers reduction of incidents resolution time as a goal.Results: By applying BPM, BPI and Process Mining we were able to discover the underlined process and a bottleneck for resolution time.Moreover, we proposed metrics to improve process and service quality by applying GQM+Strategies.